Impact of Pacific Ocean heatwaves on phytoplankton community composition

Since 2013, marine heatwaves have become recurrent throughout the equatorial and northeastern Pacific Ocean and are expected to increase in intensity relative to historic norms. Among the ecological ramifications associated with these high temperature anomalies are increased mortality of higher trophic organisms such as marine mammals and seabirds, which are likely triggered by changes in the composition of phytoplankton, the base of the marine trophic food web. Here, we assimilated satellite ocean color data into an ocean biogeochemical model to describe changes in the abundance of phytoplankton functional types (PFTs) during the last decade’s (2010s) warm anomalies in the equatorial and northeastern Pacific Ocean. We find important changes associated with the “Blob” warm anomaly in the Gulf of Alaska, where reduced silica supply led to a switch in community composition from diatoms to dinoflagellates, resulting in an increase in surface ocean chlorophyll during the Summer–Fall of 2014. A more dramatic change was observed in the equatorial Pacific, where the extreme warm conditions of the 2016 El Niño resulted in a major decline of about 40% in surface chlorophyll, which was associated with a nearly total collapse in diatoms.


Supplementary note 1 General PFT description
In the present study, an ocean biogeochemical model with explicit representation of six different phytoplankton functional types (PFTs) was employed in order to compute temporal anomalies in their Chl-based biomass and assess the relative contribution of each group to the total surface Chl concentration. Diatoms represent a group of fast-growing phytoplankton with demand for high nutrient concentrations and characterized by the formation of an outer silica shell that enhances their sinking towards greater depths. Cyanobacteria represent a functional opposite, with slow division and sinking rates, and low nutrient requirements.
Coccolithophores depict an intermediate group with moderate nutrient demands and growth S1 rates, relatively low light requirements, and relatively high sinking rates due to their calcium carbonate shell (coccoliths). Chlorophytes encompass a wide range of characteristics associated with nanoplankton, with intermediate growth and sinking rates as well as nutrient requirements. Dinoflagellates are similar to diatoms in their fast growth and high nutrient demands, but are distinguished by very high light requirements and negligible sinking rates.
Finally, phaeocystis are also characterized by relatively high light requirements and sinking rates, but present slow division rates and low nutrient requirements (Table S1 and S2).

Climatological patterns
The mean surface distribution of the main nutrients determining phytoplankton growth and the six PFTs represented in the model were computed for the entire analyzed time span

Anomalies in MLD and light limitation
We examined the relationship between anomalies in nutrients, temperature, and mixed layer depth at GOA and ENSO 3.4 ( Figure S4). In GOA, shoaling of the oceanic surface mixed layer is associated with reduced silicate concentration and warmer temperatures ( Figure S4a).
In ENSO 3.4, shallower mixed layer depths are instead associated with cool SST anomalies and high nitrate concentrations ( Figure S4b). Positive anomalies in the light growth-limiting term indicate that light limitation was reduced at GOA ( Figure S5a

Model validation Chlorophyll
Temporal anomalies in total Chl from the NOBM are compared with satellite-based anomalies obtained from MODIS and VIIRS ( Figure S6). This comparison is obtained by matching the spatial resolution of the NOBM output to that of the satellite data and masking model output in accordance with gaps in the satellite retrievals. Overall, the temporal anomaly in total Chl obtained from the NOBM is similar to that inferred from MODIS and VIIRS S3 retrievals. The skill of the model in reproducing surface satellite-based chlorophyll concentration is evaluated against global MODIS data by calculating the annual percent error (PE) for years where MODIS data for all 12 months are available (2003-2020) ( Figure S8). Globally, the PE of the model is within ± 9 % of MODIS retrievals. For the North Pacific and North Central Pacific the model PE is within ± 15 %, while the model chlorophyll PE for the Equatorial Pacific basin is within ± 12 % ( Figure S8) (see pre-defined model validation basins in Figure S7).

Phytoplankton Functional Types
In situ climatological observations are used to evaluate the skill of the model in reproducing the relative abundance of PFT with respect to total surface chlorophyll (Table S3). In situ climatological data allows for the assessment of modeled diatoms, coccolithophores, chlorophytes, cyanobacteria and phaeocystis. Globally, the largest difference in estimated relative abundance by the model is of -14.48 % for cyanobacteria, while other groups are within ± 10 %. In the North Pacific (NP), the relative abundance of diatoms and coccolithophores is overestimated in the model by (+) 30.62 % and (+) 41.18 %, respectively. The difference between modeled and in situ climatological relative abundance is much reduced for cyanobacteria (-1.03 %) and phaeocystis (-1.2 %). In the equatorial Pacific (EP), the largest difference in model-based relative abundances is of +30.9 % for chlorophytes, and -26 % for cyanobacteria, while diatoms and coccolithophores are within ± 3 %.

Nutrients
Modeled nutrient fields are validated against the observational datasets described in the  Table S1: Parameter values of phytoplankton maximum growth (division) rate (µ max ), sinking rate at 31 • C (w 0 ), and half saturation concentration for nitrate (k NO 3 ), iron (k Fe ), and silica (k Si ), set for each PFT in the NOBM. The k value for ammonium is the same as for nitrate.    Figure 5, and are shown here for reference.    Figure S7 for basins boundaries).